Identify and log dictionary vocabulary candidates with corpus-informed screening.
npx skills add https://github.com/tkgally/je-dict-1 --skill find-candidates
Please help me install this Agent Skill. Skill: find-candidates Source: https://github.com/tkgally/je-dict-1/tree/main/.claude/skills/find-candidates Command: npx skills add https://github.com/tkgally/je-dict-1 --skill find-candidates
Facilitates the systematic discovery and vetting of new vocabulary candidates to enrich candidate_words.json for dictionary expansion, reducing duplicates and maintaining editorial quality.
Ask me to start the candidate discovery process to identify and log new word candidates.
High-intent search queries and answers about installing and using this skill.
Finding new dictionary candidate words involves applying corpus-informed screening across frequency, relevance, and non-proper-noun constraints to produce a vetted list of entries suitable for general tier development.
Avoiding duplication when expanding a vocabulary dictionary requires satisfying explicit criteria checks against existing entry indices and candidate lists, ensuring previously logged words are excluded before new additions are made.
Screening corpus frequency to identify viable vocabulary candidates means evaluating word centrality and applying proper-noun exclusions, ensuring only high-quality entries matching your constraints are surfaced for editorial review.
Yes, you can add qualified words to candidate_words.json with concise notes via the manage_candidates script, integrating vetted vocabulary candidates directly into your dictionary expansion workflow.
Generating an audit-ready report for dictionary candidate additions and rejections involves producing a structured summary that details the rationale for each editorial decision, providing clear tracking for quality review.
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